Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.

Power Supply Analyzer with USB Interface

Miscellaneous Esoteric Statistical Scripts - an R package

Experimental design framework for scRNAseq population studies (eQTL and DE)

This python project is a helper package that uses power analysis to calculate required sample size for any experiment

Code used to carry out parameter estimation, correlation estimation, type 1 error analysis, and power analysis for our "Pseudoreplication in Single-Cell" study

Higher-order Masking of AES-128 based on the Rivain and Prouff method, CPRR method and Common Shares with Random Reduction method.

Blind Power Identification (DATE 2017 and Sensors 2018)

A mathematical model of the hearing process based on scientific researching

`powerly` is an R package for conducting sample size analysis for network models and more.

Simplify VLSI (timing, power, noise, correlation, reliability) modeling and analysis with Characterization Description Format

An introductory walkthrough into the concepts and workings of Power Analysis using the ChipWhisperer framework

This package underwent major revisions and is now available as powsimR!

Simulation-based power analysis library

NIST LWC Hardware Design of Ascon with Protection against Power Side-Channel Attacks

Shiny app and R package to perform a power analysis to select the number of participants in intensive longitudinal studies

A template repository for ChipWhisperer target source code in C using the SimpleSerial protocol

jamovi wrapper for pwrss package

Анализ групного датасета по игровой зависимости, проверка психологических гипотез с помощью ряда статистических методов: анализ мощности, анализ латентных классов, анова фреквентистская VS байесовская